Visualizing and Animating Movement Data

library(tidyverse)
library(sf) #for simple feature spatial data
library(mapview) #for interactive mapping
#devtools::install_github("thomasp85/gganimate")
library(gganimate) #for animations
library(knitr)
library(raster)
library(lubridate)

#load albatross data
albatross_sf <- read_tsv("data_files/Study2911040", comment="##", col_types = "Tnncc") %>% # Tnncc = time, number, number, character, character
  as.data.frame() %>%
  na.omit()  %>% 
  st_as_sf(coords = c("location_long", "location_lat"), crs=4326)

#load zebra data
zebra_sf <- read_csv("data_files/Zebra.csv") %>% 
  dplyr::select(ID = Name, 4:6) %>% 
  mutate(timestamp = as.POSIXct(lubridate::mdy_hm(Date))) %>%
  st_as_sf(., coords = 3:4, crs = "+init=epsg:4326") %>% #longlat
  st_transform("+init=epsg:32733") #convert to UTM

## Warning: Missing column names filled in: 'X1' [1]

Your typical ggplot

Let’s plot the albatross data.

# Create continental background
earth <- st_as_sf(rnaturalearth::countries110)
bbox <- st_bbox(albatross_sf, crs=st_crs(earth))
area <- st_crop(earth, bbox)

# Plot
albatross_sf %>%
  ggplot() + 
  geom_sf(aes(colour = individual_id)) +
  geom_sf(data = area, fill = 'gray') + 
  labs(title = 'Albatross tracks') + 
  theme_classic() +
  theme(panel.background = element_rect(fill = 'lightblue')) 

Interactive exploration

We will use the mapview package to make an interactive plot.

albatross_sf %>% 
  mapview(zcol="individual_id")

Let’s animate!

Animation with static background.

We’ll use the same area background as the static ggplot above but animate using the gganimate package.

anim_static <- albatross_sf %>%
  mutate(date = as.Date(timestamp)) %>%
  group_by(individual_id) %>%
  filter(!duplicated(date)) %>% #run faster by subsetting to one fix per day per individual
  ggplot() + 
  geom_sf(aes(colour = individual_id), size = 1.5) +
  geom_sf(data = area, fill = 'gray') + 
  labs(title = 'Albatross tracks', subtitle = 'Date: {format(frame_time, "%b %e %Y")}') + 
  theme_classic() +
  theme(panel.background = element_rect(fill = 'lightblue')) + 
  transition_time(date) + 
  shadow_wake(wake_length = 0.1)

movie_static <- gganimate::animate(anim_static, fps=8, height = 600, width = 700) # pause and contemplate the universe while this turns its cogs
#' fps is the framerate of the animation in frames/sec.
#' duration is the length of the animation in seconds.
#' nframe is the total number of frames.
#' detail is the number of additional frames to calculate, per frame.
#' device is the device to use for rendering the single frames( i.e., `'png'`, `'jpeg'`, `'tiff'`, and `'bmp'`). Defaults to `'png'`.
movie_static

# To download as gif:
# anim_save("albatross_static_background.gif", movie_static)

Animation with dynamic background.

For this animation we’ll overlap the 16-day NDVI layers with our zebra data in 2009.

#Load NDVI data in long format (columns for lon, lat, date, and value). For convenience I have converted it ahead of time.
NDVI_df <- read_csv("spatial_layers/NDVI_16day.csv") %>% #all of 2009
  mutate(date=as.Date(date)) %>%
  filter(date >= as.Date("2009-04-24") & date <= as.Date("2009-06-14")) %>% #reduce date range for speed
  slice(which(row_number() %% 8 == 1)) #reduce spatial resolution for speed

anim_dynamic <- zebra_sf %>%
  mutate(date = as.Date(timestamp)) %>%
  ggplot() + 
  geom_raster(data = NDVI_df, aes(x = lon, y = lat, fill = value)) +
  scale_fill_gradientn(name = "NDVI", colours=rev(terrain.colors(10))) +
  geom_sf(aes(colour = ID), size = 1.5) +
  labs(title = 'Zebra tracks', subtitle = 'Date: {format(frame_time, "%b %e %Y")}') + 
  theme_classic() +
  transition_time(date, range=c(as.Date("2009-04-28"), as.Date("2009-06-08"))) +
  shadow_wake(wake_length = 0.1) + 
  theme(legend.position="bottom")

# Warning this is verrrrry slow
movie_dynamic <- gganimate::animate(anim_dynamic, fps=5) 
movie_dynamic

# To download as gif:
# anim_save("zebra_dynamic_background.gif", movie_dynamic)